Extracting Chemical Reactions from Thai Text for Semantics-Based Information Retrieval
Summary :
Based on sliding-window rule application and extraction filtering, we present a framework for extracting multi-slot frames describing chemical reactions from Thai free text with unknown target-phrase boundaries. A supervised rule learning algorithm is employed for automatic construction of pattern-based extraction rules from hand-tagged training phrases. A filtering method is devised for removal of incorrect extraction results based on features observed from text portions appearing between adjacent slot fillers in source documents. Extracted reaction frames are represented as concept expressions in description logics and are used as metadata for document indexing. A document knowledge base supporting semantics-based information retrieval is constructed by integrating document metadata with domain-specific ontologies.
- Publication
- IEICE TRANSACTIONS on Information Vol.E94-D No.3 pp.479-486
- Publication Date
- 2011/03/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E94.D.479
- Type of Manuscript
- Special Section PAPER (Special Section on Knowledge Discovery, Data Mining and Creativity Support System)
- Category
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Peerasak INTARAPAIBOON, Ekawit NANTAJEEWARAWAT, Thanaruk THEERAMUNKONG, "Extracting Chemical Reactions from Thai Text for Semantics-Based Information Retrieval" in IEICE TRANSACTIONS on Information,
vol. E94-D, no. 3, pp. 479-486, March 2011, doi: 10.1587/transinf.E94.D.479.
Abstract: Based on sliding-window rule application and extraction filtering, we present a framework for extracting multi-slot frames describing chemical reactions from Thai free text with unknown target-phrase boundaries. A supervised rule learning algorithm is employed for automatic construction of pattern-based extraction rules from hand-tagged training phrases. A filtering method is devised for removal of incorrect extraction results based on features observed from text portions appearing between adjacent slot fillers in source documents. Extracted reaction frames are represented as concept expressions in description logics and are used as metadata for document indexing. A document knowledge base supporting semantics-based information retrieval is constructed by integrating document metadata with domain-specific ontologies.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E94.D.479/_p
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@ARTICLE{e94-d_3_479,
author={Peerasak INTARAPAIBOON, Ekawit NANTAJEEWARAWAT, Thanaruk THEERAMUNKONG, },
journal={IEICE TRANSACTIONS on Information},
title={Extracting Chemical Reactions from Thai Text for Semantics-Based Information Retrieval},
year={2011},
volume={E94-D},
number={3},
pages={479-486},
abstract={Based on sliding-window rule application and extraction filtering, we present a framework for extracting multi-slot frames describing chemical reactions from Thai free text with unknown target-phrase boundaries. A supervised rule learning algorithm is employed for automatic construction of pattern-based extraction rules from hand-tagged training phrases. A filtering method is devised for removal of incorrect extraction results based on features observed from text portions appearing between adjacent slot fillers in source documents. Extracted reaction frames are represented as concept expressions in description logics and are used as metadata for document indexing. A document knowledge base supporting semantics-based information retrieval is constructed by integrating document metadata with domain-specific ontologies.},
keywords={},
doi={10.1587/transinf.E94.D.479},
ISSN={1745-1361},
month={March},}
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TY - JOUR
TI - Extracting Chemical Reactions from Thai Text for Semantics-Based Information Retrieval
T2 - IEICE TRANSACTIONS on Information
SP - 479
EP - 486
AU - Peerasak INTARAPAIBOON
AU - Ekawit NANTAJEEWARAWAT
AU - Thanaruk THEERAMUNKONG
PY - 2011
DO - 10.1587/transinf.E94.D.479
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E94-D
IS - 3
JA - IEICE TRANSACTIONS on Information
Y1 - March 2011
AB - Based on sliding-window rule application and extraction filtering, we present a framework for extracting multi-slot frames describing chemical reactions from Thai free text with unknown target-phrase boundaries. A supervised rule learning algorithm is employed for automatic construction of pattern-based extraction rules from hand-tagged training phrases. A filtering method is devised for removal of incorrect extraction results based on features observed from text portions appearing between adjacent slot fillers in source documents. Extracted reaction frames are represented as concept expressions in description logics and are used as metadata for document indexing. A document knowledge base supporting semantics-based information retrieval is constructed by integrating document metadata with domain-specific ontologies.
ER -
English
